On the one hand, more and more decisions are being made based on what machines can learn about us: who gets a loan, who gets into college, who gets insurance, etc. On the other hand, people have many reservations about the fairness of algorithms, about algorithmic perpetuation of biases built into historical data, about the mis- or overinterpretation of statistical correlations, and more. This grant funds work by economists Jens Ludwig from the University of Chicago and Sendhil Mullainathan from Harvard to study when, why, and how people should override recommendations based on artificial intelligence. The team will focus on how New York City judges decide to release or hold suspects before trial. Machine generated recommendations—ones that use facts about a suspect to predict whether that subject will commit a crime if released back into the community—are already in use. But judges are also privy to information about a subject that a typical algorithm is not, including a suspect’s courtroom dress, demeanor, accompanying associates, etc. Ludwig and Mullainathan will study whether and how these additional factors affect both judicial predictions of suspect behavior as well as AI predictions of judicial behavior.

This grant funds efforts by Avi Goldfarb, Joshua Gans, and Ajay Agrawal, three leading economists from the University of Toronto, and Catherine Tucker, Sloan Distinguished Professor of Management at MIT, to facilitate rigorous research on the economics of artificial intelligence (AI). Building on a successful conference on the economics of AI held in Toronto in 2017, the team plans to hold a series of three more annual conferences on related topics, commissioning papers for each conference, then publishing and disseminating the collected conference proceedings. Over three years, the team anticipates commissioning more than 50 academic papers. The team will also organize extensive training, support, and other services for graduate students and postdoctoral fellows interested in studying the economics of AI. The plan is to train more than 90 early-career researchers in advanced methodological and analytic techniques.

This grant provides partial support to the National Academy of Sciences for a consensus report on how to use insights from the behavioral, social, and statistical sciences to improve the reliability and reproducibility of research. The project will include five committee meetings featuring various experts across the sciences, five commissioned papers on reproducibility, an expert panel on behavioral economics and the professional incentives facing producers and consumers of research, and a final consensus report. While the majority of the funding will be provided by NSF, this grant will provide supplementary support both for including economic perspectives in the study and for disseminating the final report.  

Between 1947 and 1973, U.S. productivity grew an average of nearly 3 percent per year. Since 2007, that rate has dropped to 1.3 percent. Since 2010, it has plummeted to 0.5 percent. China and India excepted, other countries around the world have experienced similar drops in productivity growth. Why? What is going on? This grant funds a project by a team led by Louise Sheiner at the Hutchins Center on Fiscal and Monetary Policy at the Brookings Institution to shed light on this “productivity puzzle.” Over the next two years, Brookings will conduct and commission original and rigorous research on productivity, engage with stakeholders at U.S. statistical agencies about the quality and limitations of existing productivity measurements, produce 10 to 12 peer reviewed papers, hold six conferences on this and related issues, produce a conference volume, and disseminate recommendations on how to improve research and statistics about economic productivity.

This grant provides partial support for a new report, The Future of Storage, which will bring together scientific, engineering, economic, and policy perspectives to describe the current state and future potential of technologies to store electricity and the differing roles these technologies might play in the evolving energy sector. Part of MIT’s well-regarded “Future of” series, the project will assemble a panel of top scholars from mechanical engineering, energy systems analysis, and economics to address a host of policy-relevant questions about electricity storage. Questions to be addressed by the study include what role storage might play in electricity systems over the near term (by 2030), midterm (by 2040), and long term (by 2050, and beyond); which storage technologies have the greatest potential for application over various time scales and service requirements; and what public policy, technology development, and market factors most influence the future of electricity storage. Grant funds will provide approximately one-third of the total study cost. 

The social cost of carbon (SCC) is defined as the cost to society in dollars of releasing the equivalent of one ton of carbon dioxide into the atmosphere. The SCC is a key input measure to almost every legally required cost-benefit analysis of energy and environmental regulation. To properly quantify the SCC researchers need to improve the estimation of damage functions, the models that lay out how climate changes affect the economy. The Climate Impact Lab (CIL) at the University of Chicago, partnering with scientists at the University of California, Berkeley and Rutgers University, is developing the next generation of climate-economic damage functions. The new functions are orders of magnitude more advanced than existing integrated assessment models, providing a spatially detailed, granular set of damage functions for over 25,000 regions globally. Grant funds will support development of the CIL model, its computing infrastructure, and salary support for one postdoctoral and two predoctoral fellows participating in the project.

This grant provides support to the Washington D.C.–based nonpartisan think tank Resources for the Future (RFF) to organize and host a conference that brings together researchers, policymakers, and various stakeholders to discuss the state of academic research about the economic, environmental, security, and policy trade-offs associated with the increased deployment of low- and no-carbon resources and technologies and to share research findings and insights on these issues developed by researchers funded through the Sloan Foundation’s Energy and Environment program. The conference will take place in late fall 2018, with nearly 100 participants drawn from academic, government, industry, and nonprofit sectors and will be structured as a series of research panels focused on topics such as energy efficiency, transportation, and transmission and distribution, which have become core areas of concentration within the Sloan Energy and Environment program. Additional thematic panels will be interspersed that advance methodological perspectives such as analyzing large-scale data sets and highlighting best practices to integrate research into decision-making. There will also be a dedicated session for students to present their work, along with a number of networking opportunities allowing participants to interact informally with one another. In addition to organizing and hosting the conference, RFF plans to record the event and potentially live-stream it.